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Automatic Speech Recognition (ASR)

Automatic Speech Recognition (ASR) involves converting spoken language into written text. It is designed to transcribe spoken words into text in real-time, allowing people to communicate with computers, mobile devices, and other technology using their voice. The goal of Automatic Speech Recognition is to accurately transcribe speech, taking into account variations in accent, pronunciation, and speaking style, as well as background noise and other factors that can affect speech quality.

Papers

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Showing 2751–2800 of 3012 papers

TitleStatusHype
A Text Normalisation System for Non-Standard English Words—0
A Text-to-Speech Pipeline, Evaluation Methodology, and Initial Fine-Tuning Results for Child Speech Synthesis—0
A Transfer Learning Method for Speech Emotion Recognition from Automatic Speech Recognition—0
Attacks as Defenses: Designing Robust Audio CAPTCHAs Using Attacks on Automatic Speech Recognition Systems—0
Attention-based ASR with Lightweight and Dynamic Convolutions—0
Attention based end to end Speech Recognition for Voice Search in Hindi and English—0
Attention based on-device streaming speech recognition with large speech corpus—0
Attention-based Wav2Text with Feature Transfer Learning—0
Attention Enhanced Citrinet for Speech Recognition—0
Attentive Adversarial Learning for Domain-Invariant Training—0
Attentive listening system with backchanneling, response generation and flexible turn-taking—0
A two-stage transliteration approach to improve performance of a multilingual ASR—0
A two-step approach to leverage contextual data: speech recognition in air-traffic communications—0
Audio Adversarial Examples for Robust Hybrid CTC/Attention Speech Recognition—0
Audio-attention discriminative language model for ASR rescoring—0
Audio-conditioned phonemic and prosodic annotation for building text-to-speech models from unlabeled speech data—0
Audio De-identification: A New Entity Recognition Task—0
Audio De-identification - a New Entity Recognition Task—0
Audio Enhancement for Computer Audition -- An Iterative Training Paradigm Using Sample Importance—0
Audio-visual Multi-channel Integration and Recognition of Overlapped Speech—0
Audio-visual Multi-channel Recognition of Overlapped Speech—0
Audio-visual multi-channel speech separation, dereverberation and recognition—0
Audio-visual Recognition of Overlapped speech for the LRS2 dataset—0
Audio-Visual Speech Enhancement and Separation by Utilizing Multi-Modal Self-Supervised Embeddings—0
Audio-Visual Speech Recognition is Worth 32328 Voxels—0
Audio Visual Speech Recognition using Deep Recurrent Neural Networks—0
Audio-Visual Speech Recognition With A Hybrid CTC/Attention Architecture—0
Auditory-Based Data Augmentation for End-to-End Automatic Speech Recognition—0
Augmenting Automatic Speech Recognition Models with Disfluency Detection—0
Augmenting Bottleneck Features of Deep Neural Network Employing Motor State for Speech Recognition at Humanoid Robots—0
Augmenting Images for ASR and TTS through Single-loop and Dual-loop Multimodal Chain Framework—0
A Unified Cascaded Encoder ASR Model for Dynamic Model Sizes—0
A Unified Neural Architecture for Joint Dialog Act Segmentation and Recognition in Spoken Dialog System—0
A Unified Transformer-based Framework for Duplex Text Normalization—0
A Universally-Deployable ASR Frontend for Joint Acoustic Echo Cancellation, Speech Enhancement, and Voice Separation—0
A user study to compare two conversational assistants designed for people with hearing impairments—0
Automated Cross-language Intelligibility Analysis of Parkinson's Disease Patients Using Speech Recognition Technologies—0
Automated scoring across different modalities—0
Automated speech tools for helping communities process restricted-access corpora for language revival efforts—0
Automated speech-unit delimitation in spoken learner English—0
Automatically Assess Children's Reading Skills—0
Automatic Assessment of Oral Reading Accuracy for Reading Diagnostics—0
Automatic assessment of spoken language proficiency of non-native children—0
Automatic Detection of Code-switching Style from Acoustics—0
Automatic Documentation of ICD Codes with Far-Field Speech Recognition—0
Automatic Estimation of Intelligibility Measure for Consonants in Speech—0
Automatic language identity tagging on word and sentence-level in multilingual text sources: a case-study on Luxembourgish—0
Automatic Learning of Subword Dependent Model Scales—0
Automatic Quality Estimation for ASR System Combination—0
Automatic recognition and detection of aphasic natural speech—0
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All datasetsLRS2RealMANSagaleeHUI speech corpusLRS3-TEDM-AILabs speech datasetThe Spoken Wikipedia CorporaVoxforge GermanVoxPopuli

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TM-CTCTest WER10.1—Unverified
2TM-seq2seqTest WER9.7—Unverified
3CTC/attentionTest WER8.2—Unverified
4LF-MMI TDNNTest WER6.7—Unverified
5Whisper-LLaMATest WER6.6—Unverified
6End2end ConformerTest WER3.9—Unverified
7End2end ConformerTest WER3.7—Unverified
8MoCo + wav2vec (w/o extLM)Test WER2.7—Unverified
9CTC/AttentionTest WER1.5—Unverified
10WhisperTest WER1.3—Unverified
#ModelMetricClaimedVerifiedStatus
1SpatialNetCER14.5—Unverified
2CleanMel-L-maskCER14.4—Unverified
#ModelMetricClaimedVerifiedStatus
1ConformerTest WER15.32—Unverified
2Whisper-largev3-finetunedTest WER10.82—Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)1.89—Unverified
#ModelMetricClaimedVerifiedStatus
1DistillAVWER1.4—Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)4.28—Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)8.04—Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)3.36—Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer Transducer (German)WER (%)8.98—Unverified